Research Scientist / Engineer – Machine Learning (Contractor)

About Huawei Research and Development UK Limited Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over 170 countries and regions, serving more than three billion people around the world. Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world.

Huawei Research and Development UK Limited Overview Huawei's vision is a fully connected, intelligent world. To achieve this, we work to inspire passion for basic research around the world. Our combined passion drives development across the global innovation value chain. Huawei has the largest Research and Development organization in the world with 96,000+ employees in research centers around the globe. In the UK, we already have design centers in Cambridge, London, Edinburgh and Ipswich.

Job Summary The Reinforcement Learning Team at the London Office of UKRD is seeking a highly skilled Machine Learning Scientist / Engineer to join our team. Our group combines world-class research with impactful applications, earning top honors such as NeurIPS 2020 Black Box Optimisation Challenge - Winners, multiple Best Paper Awards, and industry recognition. This role focuses on advancing the state-of-the-art in reinforcement learning (RL), Bayesian optimisation (BO), AI agents, large language models (LLMs), and vision-language models (VLMs).

• Key Responsibilities:
• Research & Development: Design, implement, and evaluate novel algorithms and architectures in RL, BO, AI agents, LLM tuning, or VLMs for reasoning, planning, and decision-making under uncertainty.
• System Implementation: Translate cutting-edge research concepts into working prototypes, scalable systems, and applications (e.g., AI for science, chemistry, physics, open math problems, robotics).
• Publications & Open Source: Conduct original research and engage with the scientific community through publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, JMLR) or open-source contributions.
• Cross-functional Collaboration: Partner with multidisciplinary teams to integrate research models into production environments and broader strategic initiatives.
• Adaptability & Innovation: Drive technical problem-solving across diverse or emerging domains outside your primary area of expertise when business needs evolve.

This job description is only an outline of the tasks, responsibilities and outcomes required of the role. The jobholder will carry out any other duties as may be reasonably required by his/her line manager.

Person Specification:

• Required Qualifications
• Education: Master's or PhD (completed or in progress) in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• Core Technical Expertise: Demonstrated expertise in AI/ML topics, specifically Reinforcement Learning or LLM tuning/alignment (evidenced by peer-reviewed publications, open-source code, or technical portfolio projects; standard coursework alone is not sufficient).
• Engineering & Math Foundation: Strong mathematical understanding of core AI approaches, high proficiency in Python, and hands-on experience with PyTorch (or JAX/TensorFlow).
• Domain Adaptability: Proven track record of technical versatility—ability to quickly adapt, learn, and deliver impact in new domains or projects outside your core specialization.
• Environment: Ability to thrive in a fast-paced, research-driven environment with ambiguous, evolving objectives.

• Preferred Qualifications
• First-author publications in top-tier venues (NeurIPS, ICML, ICLR, JMLR, etc.).
• Hands-on experience with RL fine-tuning frameworks (e.g., TRL, verl) and distributed multi-GPU training.
• Active GitHub portfolio demonstrating applied ML/AI implementations or system engineering.